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Coreference Resolution is a well studied problem in NLP. While widely studiedfor English and other resource-rich languages, research on coreferenceresolution in Bengali largely remains unexplored due to the absence of relevantdatasets. Bengali, being a low-resource language, exhibits greatermorphological richness compared to English. In this article, we introduce a newdataset, BenCoref, comprising coreference annotations for Bengali textsgathered from four distinct domains. This relatively small dataset contains5200 mention annotations forming 502 mention clusters within 48,569 tokens. Wedescribe the process of creating this dataset and report performance ofmultiple models trained using BenCoref. We expect that our work provides somevaluable insights on the variations in coreference phenomena across severaldomains in Bengali and encourages the development of additional resources forBengali. Furthermore, we found poor crosslingual performance at zero-shotsetting from English, highlighting the need for more language-specificresources for this task.

BenCoref: A Multi-Domain Dataset of Nominal Phrases and Pronominal Reference Annotations